The field of communications has become increasingly important in today's society. One area of importance associated with network communications relates to network routing. Routing protocols allow one or more components, devices, or modules to correctly direct information to its appropriate next destination. Certain paths or designated routes may be considered optimal or preferred over others.
As traffic and the subscriber base of end users increases, so too does the importance of efficient management of communication sessions and data flows. In order to assist in this endeavor, service providers generally utilize a tool known as a traffic matrix. The traffic matrix offers a summary of traffic volume between any two or more selected network elements. Traffic volume can provide some idea to service providers about capacity considerations between network elements, packet loss characteristics in the network, or other network aspects to be considered. The traffic matrix can offer a valuable tool for service providers to allocate their resources in an optimal fashion.
Existing methodologies and strategies to create a traffic matrix suffer from a number of shortcomings. For example, architectures simply take too long to deduce the traffic matrix for a given service provider. Moreover, many operations that produce a traffic matrix require intensive and complex calculations. Further, existing traffic matrix solutions consume excessive resources in executing their assigned operations. Thus, the ability to quickly and accurately create a suitable traffic matrix in a network environment provides a significant challenge to network operators, service providers, and system designers.